A mission-oriented approach
to building the entrepreneurial state
Mariana Mazzucato
November 2014
InnovateUK_InnovationPolicy_T14-165_2.indd 1
30/10/2014 14:49
Innovate UK commissioned this
thought leadership piece to inform
our strategic development of
innovation support and promote
further discussion in this area.
This work belongs to Professor
Mazzucato and is not intended to
reflect the views of Innovate UK.
Mariana Mazzucato (PhD) holds
the RM Phillips chair in the
Economics of Innovation at SPRU in
the University of Sussex. Previously
she has held academic positions at
the University of Denver, London
Business School, Open University,
and Bocconi University.
Innovate UK is the new name for
the Technology Strategy Board –
we’re the UK’s innovation agency,
accelerating economic growth.
Her research focuses on the
relationship between financial
markets, innovation, and economic
growth – at the company, industry
and national level. Between 20092012 she directed a large 3 year
European Commission FP7 funded
project on Finance and Innovation
(FINNOV); her current project
on Financing Innovation is funded
by the Institute for New Economic
Thinking (INET); and her project
on Finance and Mission Oriented
Investments is funded by the Ford
Foundation’s Reforming Global
Financial Governance initiative.
We know that taking a new idea
to market is a challenge. We fund,
support and connect innovative
businesses through a unique mix
of people and programmes to
accelerate sustainable economic
growth.
www.innovateuk.gov.uk
Her new book The Entrepreneurial
State: debunking private vs. public
sector myths (Anthem, 2013) was
shortlisted for the prestigious
Wirtschaftsbuchpreis in Germany
and on the 2013 Books of the Year
list of the Financial Times, and
Forbes. It focuses on the need to
develop new frameworks to
understand the role of the state in
economic growth – and how to
enable rewards from innovation to
be just as ‘social’ as the risks taken.
Professor Mazzucato is winner of
the New Statesman SPERI Prize in
Political Economy and in 2013 the
New Republic called her one of the
‘3 most important thinkers about
innovation’. She advises the UK
government and the EC on
innovation-led growth. Her research
outputs, media engagement, and
talks (including her TED Global talk),
can be found on her website.
www.marianamazzucato.com
@MazzucatoM
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A mission-oriented approach
to building the entrepreneurial state
Mariana Mazzucato
RM Phillips Professor in the Economics of Innovation
Science Policy Research Unit, University of Sussex, UK
www.marianamazzucato.com
© Mariana Mazzucato
Abstract
Many western countries are pursuing innovation-led ‘smart’ growth so to rebalance away from
consumer debt driven growth and ‘financialization’. This paper argues that innovation-led growth
is a major battle that requires public policy to fundamentally change from one that views the goal
of government as simply fixing markets to one that views it in terms of actively creating and
shaping markets. Indeed, those ‘mission-oriented’ investments that led to putting a man on the
moon (with the resulting technological spill-overs) - and are today catalysing investments to tackle
climate change world-wide - required dynamic public agencies to be active in shaping and creating
new market landscapes. The paper considers four key questions which arise from such a ‘market
creating’ framework: decision-making on the direction of change; the nature of (public and
private) organisations that can welcome the underlying uncertainty and discovery process; the
evaluation of mission-oriented and market creation policies; and the need to share both the risks
and rewards underlying the innovation process—so that ‘smart’ innovation-led growth can also
become ‘inclusive’ growth. The paper is meant to serve as a ‘think piece’ for Innovate UK so that it
can think more broadly and strategically about its role at the centre of the economic growth
process.
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1. Introduction
How to deliver smart, sustainable economic growth is the central question facing developed
economies today. In the UK, the debate has focused on how to rebalance away from consumer
debt driven growth towards a smarter, innovation-led growth model. This battle is enormous. It
requires bringing innovation to the centre of growth policy—and in doing so, radically rethinking
the traditional role of government and public policy in the economy. In essence, we need a new
policy framework which is about market making and market shaping, not just market fixing. It also
requires making sure the private sector is equally committed to investing in innovation, reversing
the current trend towards ‘financialization’ in which many companies are spending more on
boosting short term stock prices than on investing in long run areas.
This paper reflects on the reasons why market failure theory in economics, used by policy makers
world wide, results in a limited framework to justify the type of policies that are needed to allow
innovation to become central to growth policy, and, in turn, agencies like Innovate UK (the new
name for the Technology Strategy Board) to become central to that activity. Growth depends on
all aspects of demand: private consumption, private business investment, government spending
and net exports. Much of innovation policy is aimed at measures directed at getting the private
sector to increase their investments in innovation. This is especially problematic in countries like
the UK that are characterised by low gross R&D spending to GDP (GERD, Figure 1) and also low
business spending to GDP (BERD, Figure 2). Yet such measures are often too indirect, assuming
that all that is needed are incentives, through different types of tax incentives (e.g. R&D tax
credits). Evidence instead suggests that business tends to invest seriously in innovation only when
market and technological opportunities are in sight. And the latter are strongly correlated with
direct (not indirect) government investments in new areas characterised by high capital intensity
and high technological and market risks. These investments have not been driven by the need to
‘fix’ narrow market failures, but by the mission to solve societal and technological challenges. The
paper argues that understanding this dynamic requires a policy framework that is geared towards
shaping and creating markets not only fixing them.
Innovation-led growth requires investing in key innovation ‘inputs’, such as Research &
Development (R&D), and building dynamic ‘systems’ of innovation that allow new knowledge and
innovation to diffuse throughout the entire economy. Systems and eco-systems of innovation
(sectoral, regional, and national) embody dynamic links between the different innovation actors
and institutions (firms, financial institutions, research/education, public sector funds, intermediary
institutions) as well as horizontal links within organisations and institutions (Freeman, 1995). In
countries that have achieved innovation-led ‘smart’ growth, such institutions have been essential
for not only fixing ‘market failures’, and ‘system failures’, but for also actively shaping and creating
new markets (Mazzucato, 2013a).
Innovate UK is a fundamental part of the UK innovation system of innovation. Part of its mission is
indeed to help achieve the dynamic links between firms, the science base and of course financial
institutions. This paper argues that for Innovate UK, and other UK innovation agencies, to have a
central role in innovation-led economic growth, it is essential for its policies to go beyond the
market failure framework (explained in Section 3) which continues to justify policy intervention in
different domains. What is needed is a ‘market creation’ framework. John Maynard Keynes argued
that “Practical men, who believe themselves to be quite exempt from any intellectual influence, are
usually the slaves of some defunct economist” (Keynes, 1934, p. 383). Indeed, it will be argued
there that a market creation framework requires policy makers to be freed from the shackles of
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market failure theory. Only in this way will innovation go to the heart of economic growth policy,
rather than be side-lined to (politically) unstable areas of industrial policy.
Figure 1 Gross R&D spending as a percentage of GDP (source: OECD)
Figure 2 Business R&D spending as a % of GDP (source: OECD)
For innovation to become central to growth policy the UK Treasury and the UK Department for
Business Innovation and Skills (BIS) must work together more coherently and consistently. Yet
there has been a lack of connection between centrally directed fiscal policy and policies around
innovation and industrial strategy. Emerging evidence that the spending multiplier is higher when
spending is ‘directed’, creating dynamic spill-overs between technological development,
productivity, and job creation (Tassey, 2012)—is indeed the micro–macro connection that is
missing in modern-day economics. Productive investments generate growth, and when
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spending is more ‘directed’ towards broadly defined areas like IT in the 1980s and 1990s, and the
green economy today, the multiplier effect is stronger. As Tassey (2012) argues:
“…the highest order problem is the long-term inadequacy of productivity enhancing investments
(technology, physical, human and organizational capital). Increasing the demand for housing does
have a multiplier effect on that industry’s supply chain, but this effect pales compared to the leverage
from investment in technology for hardware and software that drive productivity in many
industries. Equally important, the jobs created by a technology-driven supply chain are much higher
paying – but, they must be sustained over entire technology life cycles.” (Tassey 2012, p.31)
Bringing innovation to the heart of growth policy means allowing agencies like Innovate UK to
consider alongside the Treasury the ways to allow money creation and spending to be more
‘directed’. Is it enough for government policy to ‘create the horizontal conditions’ for innovation
(education, research and infrastructure), and ‘facilitate’ innovation in the private sector, and wait
for the ‘market’ to decide the direction of that change? Or must the public sector also be
innovative itself, invest in its own capacities and resources, and actively invest in particular areas
that determine the directions of change—setting the boundaries within which private sector
innovation and experimentation happen? These questions bring us to the heart of the criticisms
about ‘picking winners’ and ‘crowding out’ which are often directed at agencies like Innovate UK,
or any active public sector agency, which is seen as going beyond fixing narrow market failures
(e.g. the BBC is also accused of crowding out private broadcasters in an existing market, without
indicators of its market shaping role).
The question on directionality (choosing areas of change, rather than just ‘facilitating’ it) are
crucial because innovation has both a rate and a direction (Stirling, 2008). While there is much
discussion about the former, the latter raises concerns about ‘picking winners’. Yet as I argue in
The Entrepreneurial State: debunking public vs. private sector myths (Mazzucato, 2013a), every
technology that makes the iPhone a ‘smart’ phone, was indeed picked and funded by government
(see Figure 3 for public investments that led to GPS, Internet, touch screen display, and the SIRI
voice activated system). This is also true of many high tech firms like Compaq and Intel, which
received early stage financing not from private venture capital, but from agencies like the Small
Business Innovation Research Programme of the US government (Mazzucato, 2013a), or
equivalent programmes like Yozma in Israel, or SITRA in Finland. Indeed, with the increasing shorttermism of private venture capital (seeking an exit in 3 years while innovation can take 15-20
years), such public finance has become even more important over time even in developed
economies (Mazzucato and Penna, 2014; Mazzucato and Perez, 2014).
Figure 3 Public investments that make the iPhone ‘smart’ (source Mazzucato, 2013a, p. 109)
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The worry about ‘picking winners’ thus ignores that choices have always been made, and it was
these choices that allowed new sectors to emerge, from the internet economy to the
biotechnology industry and today’s developments in both nanotechnology and clean-technology.
Even the recent advances in shale gas (fracking) were funded initially by government, which
‘chose’ that trajectory (Breakthrough Institute, 2013). Picking does not have to imply a ‘top down’
bureaucratic process. It can be a dynamic decentralised process led by a host of different types of
public institutions. In the UK, it would include agencies like the Medical Research Council
(responsible for the greatest advancements in molecular antibodies), and the Innovate UK. In the
US this would include a wide variety of institutions from the National Science Foundation (NSF),
the National Institutes of Health (NIH), Advanced Research Projects Agency (in both defence,
DARPA, and energy, ARPA-E) and the National Nanotechnology Initiative (NNI) (Block and Keller,
2012). Figure 4 shows the wide variety of public organisations that have been very active along the
entire innovation chain in the USA. A classic market failure framework has difficulty in justifying
such active policy which includes not only investments in ‘public goods’ like basic research (e.g.
NSF), but also applied research (e.g. ARPA-E) and early stage seed financing of companies (SBIR,
Small Business Innovation Research)—ie investments along the entire innovation chain. Indeed, as
can be seen in Figure 5 the scale of public SBIR funding has increased over the course of the years,
precisely because private venture capital has become more short-termist (Mazzucato 2013b).
Neither the breadth of such policy making nor the depth (with the National Institutes of Health
spending close to $32 billion per year) can be justified from the classical market failure approach.
Indeed, market enthusiasts often accuse such organisations of ‘crowding out’ private sector
activity, an argument we return to below after considering the limitations of the market failure
framework and its implications for evaluation of public investments.
Figure 4 Public and private investments along innovation chain
(source: author’s addition of public agencies to underlying figure by Auerswald and Branscomb 2003)
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Figure 5 Number of SBIR grants compared to private venture capital (source: Block and Keller, 2012)
Not only do these institutions work closely with scientists in universities, but when they are also
able to attract expertise and talent within their organisations, the process of decision making is
science led not ‘bureaucracy led’. Indeed, the fact that the Department of Energy in the USA was
until recently led by a Nobel Prize winning physicist (Dr. Steven Chu) is tightly correlated with the
fact this agency is mission-oriented and it’s an ‘honour’ for a scientist to lead it. Under his
leadership, ARPA-E was formed, which is today trying to stimulate innovation in renewable energy
as DARPA did in information technology—investing in the high risk projects that the private sector
wont fund. Such investments are often directed via procurement, thus pushing both on the supply
side and the demand side. The latter is key for creating the ‘market’ for technologies which then
stimulate further private sector activity, given that business tends to only invest when clear
market opportunities are in sight.
Directionality has often been led by socio-economic ‘challenges’ or technological ‘missions’, which
created general purpose technologies (Ruttan, 2006). And the deployment of these technologies
was also affected by policies, such as the role that suburbanization (policies) had on the diffusion
of the mass production revolution (Mazzucato and Perez, 2014). This paper will reflect on the
lessons to be learned about the scale and scope of directed innovation policy from ‘missionoriented policies’ that were aimed at security concerns, and more recently socio-economic
concerns around health and energy (Mowery, 2010; Foray et al. 2013).
This is not a traditional paper about innovation policy. It does not aim to provide narrow answers
to narrow questions (e.g. what type of science industry links to produce), but to provide a fresh list
of new questions that arise from positioning innovation policy in a market creation framework.
The key areas of discussion will be around the ‘direction’ of change, the organisational dynamics
needed to foster such change, new measures to evaluate ‘transformational’ public investments,
and the distribution of risks and rewards between the public and private sectors so that the
growth that ensues is not only ‘smart’ but also more ‘inclusive’.
The paper is structured as follows. Section (2) considers the context of challenge driven innovation
for the key question about directionality, and finishes with the related questions on organisations,
evaluation and rewards. Section (3) reviews the market failure framework in detail so that moving
beyond it is based on a clear understanding of the way it directs different types of innovation
policies (from financing public goods like basic research to seed financing subject to asymmetric
6
information). Section (4) uses insights from various (heterodox) literatures in economics for
moving beyond the market failure framework, and towards a market creation framework. Section
(5) uses these insights to pose new challenges for the role of active market creating agencies like
Innovate UK in the UK.
2. Societal Challenges and opportunity driven investments
Innovation agencies in countries or in transnational organisations like the European Commission,
are increasingly considering the socio-economic-technological ‘challenges’ for innovation policy
(see the Innovation Union Flagship Initiative in the EC2020 strategy). Whether these challenges
are the battle against climate change or the demographic-ageing crisis, the idea is that innovation
policy should produce solutions for societal problems and missions.
A key goal for this think piece is to allow such challenge driven innovation policy to be guided by a
new economic policy framework that can guide the way in which policy makers envision the
transformational changes required (catalytical and radical, as well as the more incremental), take
the associated risks (as most attempts will fail), and organise the institutions needed to manage
the underlying exploration, learning and uncertainty. The framework proposed here draws on and
advances an analysis and ‘narrative’ of the role of public policy in the economy that differs from
that of traditional market failure policy framework in economics.
Societal challenges such as climate change, youth unemployment, obesity, ageing, and rising
inequality have helped form a new agenda for innovation and growth policy that requires
politicians and policymakers to ‘think big’ about what kind of technologies and socio-economic
policies can fulfil visionary ambitions to make growth more ‘smart’, ‘inclusive’ and ‘sustainable’
(EC Innovation Union; OECD Innovation Strategy). Although such challenges are not strictly
technological (and in fact require also behavioural and systemic changes), they have much to learn
from those ‘mission-oriented’ feats that led to putting a man on the moon, or to those that led to
the emergence of new general-purpose technologies, from the Internet to biotechnology and
nanotechnology (Foray et al., 2012; Ruttan, 2006). Achieving those missions required the public
and private sectors to work together to create new technologies and sectors. Most of all, they
involved a confident state that was able and willing to courageously envision the direction of
change-defining missions and to organise institutional structures across public agencies and
departments. They entailed a state that welcomed the associated risks and extreme uncertainties
across the entire innovation chain (not only the upstream basic research), and the
experimentation processes required for organisational learning (Mazzucato, 2013a; Rodrik, 2013).
Today’s societal challenges, which combine social, political, economic and technological ambitions,
are indeed the new ‘missions’, which necessitate a similar if not greater level of visionary
investment and state capacity. Yet, we are living through a crisis of imagination with regard to the
role of the state in the economy—what Judt (2011) called a ‘discursive’ battle. By limiting our
understanding of the role of the public sector to one that simply ‘administers’, ‘fixes’, ‘regulates’,
‘spends’, ‘meddles’, and at best ‘facilitates’ and ‘de-risks’ the private sector, we are unable to
think creatively about how to allow public sector vision, risk-taking and investment to lead and
structure the needed transformational changes. This ‘think piece’ paper seeks to provide a new
framework through which such vision and ambition can be formulated, guided, organised,
evaluated and managed.
Key to the problem is that the prevailing policy framework in economics justifies state intervention
only if it is geared towards fixing situations in which markets fail to ‘efficiently’ allocate resources.
This market failure approach suggests that governments intervene to ‘fix’ markets by investing in
areas with ‘public goods’ characteristics (such as basic research, or drugs with little market
potential) and by devising market mechanisms to internalise external costs (such as pollution) or
7
external benefits (such as herd immunity). According to this approach, the state should only aim to
fix a market failure if such an action does not lead to an even worse outcome due to ‘government
failure’ (Tullock et al., 2002). For instance, the state should intervene in a way that does not
displace (‘crowd out’) private enterprise, which is judged to be superior in selecting and managing
investments (Friedman, 1979). In other words, the state should not ‘direct’ the economy or try to
‘pick winners’; it should step back and concentrate on facilitating private initiative and ‘optimising’
market performance to maximize the rate of progress.
The market failure framework is problematic for addressing societal challenges because it cannot
explain and justify the kinds of transformative mission-oriented investments that in the past
‘picked’ directions, coordinated public and private initiatives, built new networks, and drove the
entire techno-economic process, thus resulting in the creation of new markets—not just in the
fixing of existing ones. The market failure approach is more useful for describing a steady state
situation in which public policy aims to put patches on existing development trajectories provided
by markets, but not to dynamically create and shape new trajectories. The main problem is that
market failure theory does not embody any justification for the kind of mission-oriented
directionality (and ‘routes’ within directions) that was required for innovations such as the
Internet and nanotechnology, and is required today to address societal challenges ranging from
climate change to the ageing crisis. Secondly, because it lacks a clear framework that posits the
objective of state policy to create and shape markets, market failure theory cannot evaluate and
assess such mission-oriented investments when they happen. Thirdly, by not describing the state
as a lead risk-taker and investor in this process, market failure theory has avoided a key question
regarding the distribution of risks and rewards between the state and the private sector. Fourthly,
by not considering the state as a lead investor and market creator, market failure theory has not
produced insights about the type and structure of public sector organisations that are needed to
provide the depth and breadth of high-risk investments.
The paper addresses these four challenges, by asking the following questions:
(1) How can public policy be understood in terms of setting the direction and route of change;
that is, shaping and creating markets rather than just fixing them (DIRECTIONALITY)?
(2) How should public organisations be structured so they accommodate the risk taking and
explorative capacity, and the capabilities needed to envision and manage contemporary
challenges (ORGANISATIONS)?
(3) How can this alternative conceptualisation be translated into new indicators and evaluation
tools for public policies, beyond the micro-economic cost/benefit analysis and macroeconomic appraisal of crowding in/crowding out that stem directly from the ‘market failure’
perspective (EVALUATION)?
(4) How can this alternative conceptualisation be put into practice so that it results in the
socialisation of risks, but also of rewards, enabling ‘smart growth’ to also be ‘inclusive growth’
(RISKS and REWARDS)?
While the questions may seem broad, it is their connection that lies at the centre of a market
creation framework. Policy aiming to actively create and shape markets, requires indicators which
assess their performance along that particular ‘transformational’ objective. The state’s ability and
willingness to take risks, embodied in transformational changes, requires an organisational culture
(and policy capacity) which welcomes the possibility of failure and experimentation, and which is
rewarded for ‘successes’ so that ‘failures’ can be covered and the next round repeated.
This alternative view (policy framework) of policy making builds on the inspirational work of Karl
Polanyi (2001 [1944]), an economic historian and sociologist who understood markets as being
deeply embedded in social institutions, with policy not standing on the sidelines but within the
very market creation process. In his epic book The Great Transformation, he described the way in
8
which capitalist markets are deeply ‘embedded’ in social and political institutions, rendering
meaningless the usual static state vs. market juxtaposition: “[t]he road to the free market was
opened and kept open by an enormous increase in continuous, centrally organized and controlled
interventionism” (2001 [1944], p. 144). It also builds on John Maynard Keynes’ challenge for
governments to think big: “The important thing for Government is not to do things which
individuals are doing already, and to do them a little better or a little worse; but to do those things
which at present are not done at all” (Keynes, 1926, p. 46). This view of policy has implications for
the transformational effect of government policies, not found in macroeconomic interpretations
of Keynes’ work.
Before considering an alternative analysis, it is crucial to understand the market failure framework
on its own grounds.
3. MARKET FAILURE THEORY
The market failure justification of government involvement in the economy is the prevalent
framework used by policy makers around the world in various policy domains, from education to
health, infrastructure and innovation. While useful insights have been derived from this
framework, I will show it is limited in its ability to provide guidance for transformational
objectives. Throughout this proposal we take the term ‘transformational’ policies to mean the way
in which policy can actively shape and create markets, not just ‘fix’ them.
Market failure theory takes the ‘First Fundamental Theorem’ (FFT) of welfare economics (Arrow,
1951) as the starting point. The FFT states that markets are the most efficient allocators of
resources under three specific conditions: (1) There is a complete set of markets, so that all
supplied/demanded goods and services are traded at publicly known prices; (2) all consumers and
producers behave competitively (that is, all agents are price-takers); and (3) an equilibrium exists.
Under these three conditions, the allocation of resources by markets is Pareto optimal (no other
allocation will make a consumer or producer better off without making someone else worse
off). Violations of any of the three assumptions lead to inefficient allocation of resources by
markets—that is, market failures. If markets are not Pareto efficient, then everyone could be
made better off through public policies that correct the market failure. Within this framework,
market failure is only a necessary but not sufficient condition for governmental intervention (Wolf,
1988). The sufficiency results from an assessment that the gains from the intervention outweigh
the associated costs due to ‘governmental failures’ (Tullock et al., 2002), such as capture by
private interests (nepotism, cronyism, corruption, rent-seeking) (Krueger, 1974), misallocation of
resources (for example, ‘picking losers’) (Falck et al., 2011), or undue competition with private
initiatives (‘crowding out’) (Friedman, 1979).
Thus, there is a trade-off between two inefficient outcomes, one generated by free markets
(market failure) and the other by governmental intervention (government failure). The solutions
advocated by Neo-Keynesians focus on correcting failures such as imperfect information (Stiglitz &
Weiss, 1981). Solutions advocated by Public Choice scholars (Buchanan, 2003) focus on leaving
resource allocation to markets (which may be able to correct their failures on their own). We
argue here that such solutions might hold for steady state situations, but not for the situations in
which public policy is required for large technological and socio-economic missions. Such missions
require an emphasis not on fixing market failures or minimising government failures but on
maximising the transformative impact of policy that can shape and create markets.
Four broad categories of market failures can be described, according to the source of failure (and
hence what needs ‘fixing’) and which condition of the FFT it violates. These are described below.
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MF1. Coordination failures. These occur when agents fail to coordinate their expectations and
preferences throughout the business cycle so that markets fail to reach an equilibrium (supply
does not match demand; workers do not find employment; savings do not get invested). Business
cycles create an intertemporal dynamic, which make it difficult to coordinate expectations and
preferences, giving rise to situations in which the economy follows a Pareto-inefficient path
(Stiglitz, 1974). In such situations, capital, labour and natural resources will be underutilised,
because supply and demand for them do not match (Bator, 1958; Stiglitz, 1991). From this
perspective, government intervention would be justified as a way to address the ‘coordination
failure’ that arises from private agents’ (such as banks and firms) being too pro-cyclical (lending
and investing too much in the boom and too little in the bust), putting the economy on a
downwards path. Therefore, market failure theory assumes that the state is ‘risk-neutral’ and
capable of absorbing risk during an economic crisis, spreading risk over time and cross-sectionally
(Arrow & Lind, 1970). It is this assumption that justifies the promotion of countercyclical fiscal and
monetary policies. For instance, in times of crisis, greater risk aversion of private agents may lead
to underinvestment. To address this issue, the state may increase public investment to provide
short-term fiscal stimulus to keep the economy running, or it may decrease interest rates in order
to indirectly de-risk private investments. In this view, directionality is provided by markets. An
implicit corollary of this ‘coordination failure’ intervention is that if the public sector invests too
much during a boom, it risks crowding out private finance, particularly if investments are debtfinanced (Friedman, 1979), but not only in such cases (for example, crowding out can also occur if
public investment leads to changes in exchange rates). In such situations, it may be that ‘fiscal
consolidation’ (austerity measures; contractionary fiscal policy) will result in expansion of private
investments (Giavazzi & Pagano, 1990).
MF2. Public good failures (for example, provision of clean air or new knowledge) and situations of
imperfect competition (for example, natural monopolies, network effects, supply and demandside economies of scale). These are both key reasons for industrial policies. Wherever private
lenders have limited incentives to finance projects with ‘public good’ characteristics (nonexcludable and non-rival), or in situations of imperfect competition, the market is not an efficient
allocator of resources, and therefore state intervention is justified. Examples include private
markets underfunding of goods with very high spillovers (such as basic research that generates
new knowledge) or socially desirable infrastructure projects with positive externalities—both are
characterised by value that cannot be internalised by private agents. Research and development
(R&D) investments generate new knowledge, which cannot be fully appropriated by the original
investor (who cannot ‘exclude’ other agents from using the knowledge to their own benefit). Thus,
private agents tend to underinvest in R&D and innovation, because they cannot internalise
benefits that would compensate for the development costs and make the investments
worthwhile. Competition failures arise when there are high natural barriers to entry (due to scale
economies or network effects), which also lead to Pareto-inefficient situations (Stiglitz, 1991). In
order to correct for these kinds of market failures, the state may invest in early stage blue sky
research, infrastructure and other public works, enforce competition policies, regulate natural
monopolies, establish early technical standards, and so on. Indeed, what links these potential
sources of failures is that they all focus on using macro industrial policies to promote investments
in public goods that are under-produced in prevailing market conditions or tackle situations of
monopoly and monopsony (by promoting the entry of new agents to increase the pool of
producers and consumers or avoiding collusion, thus fostering competition). In order to minimise
the risk of governmental failure, innovation policies are often designed to be ‘neutral’, so as to not
favour or disfavour specific private agents. This view became dominant in the 1990s, when
‘diffusion-oriented’ policies (focused on ‘getting the conditions right’) replaced ‘mission-oriented’
technology policies (Chiang, 1991). In the diffusion-oriented paradigm, policies to promote the
supply of public goods are supposed to create the ‘right conditions’ for innovation. This is done,
10
for example, by de-risking the private sector (through tax incentives) not ‘picking winners’. This
expression is commonly used to describe policies which are strongly directive, benefitting specific
firms, technologies and sectors, which many believe will inevitably lead to government failure
(Falck et al., 2011).
MF3. Information failures arising from incomplete markets with high transaction costs and
information asymmetries; for example, bad vs. good borrowers (leading to adverse selection or
moral hazard behaviours). Such market failures take place at a more microeconomic level, creating
inefficiencies associated with non-equilibrium situations that result from the interaction between
agents (microeconomic exchanges). For example, microeconomic Pareto inefficiencies may be
caused by information asymmetries that lead to adverse selection of potentially good borrowers
(Stiglitz & Weiss, 1981); or they may be the result of high costs to carry out a transaction through
markets (Coase, 1960). Classic examples are the lack of finance for small enterprises or for R&D
and innovation projects—both of which are risky and uncertain. Underinvestment in R&D projects
due to information asymmetries can even occur in the presence of strong intellectual property
laws, macroeconomic stability, free-trade, and contract enforcement, because markets are
‘incomplete’ (Stiglitz, 1991). In these situations, public investment in SMEs and innovation,
through loans, equity or grants, would be justified in order to promote economic diversification,
growth and development. To minimise risks of government failure through capture by private
interests or of crowding out, the preferred policies should be ‘neutral’ and simply ‘de-risk’ the
private sector across the board, without picking favourite firms or sectors.
MF4. Negative externalities arising from the production or use of goods and services such as
climate change, traffic congestion, or antibiotic resistance, for which there is no market. In this
perspective, most societal challenges are seen as negative externalities. Such failures work at the
system level; that is, they amount to ‘system failures’. The socio-economic system as whole results
in ‘costly’ outcomes that are undesirable from a societal point of view. For instance, climate
change can be seen as a negative externality from carbon-intensive production methods or the
burn of fossil fuels. Indeed, the Stern Review (Stern, 2006) on the economics of climate change
states that: “Climate change presents a unique challenge for economics: it is the greatest example
of market failure we have ever seen” (Stern, 2006, p. 1). Negative externalities are not reflected in
the price system: there is no ‘equilibrium’ price because there is no market for negative
externalities. Economists often call for market-based mechanisms (such as carbon pricing or
carbon taxes) or neutral technology policies (such as tax breaks) to correct for this type of market
failure, both of which would minimise the risk of government failure by leaving the direction of
change to be determined by market forces.
The key contention of this paper is that while market failure theory is useful for addressing some
of the confined areas above, it cannot explain and justify the more ambitious role that the state
has historically played in shaping and creating markets, not just fixing them: transforming them.
Behind the investments that led to key ‘technological revolutions’ and ‘general-purpose
technologies’ was the active hand of the state: the ‘mass production’ system, aviation and space
technologies, nuclear power, information technologies and electronics, and the Internet (Ruttan,
2006). The investments that led to the Internet, for example, were not confined to public goods
areas: their breadth covered the entire innovation chain from basic research to applied research
and early-stage financing of companies (Block and Keller, 2011). These investments, like those that
lay behind nanotechnology and biotechnology, were driven by a vision to create new markets, not
to fix ‘network externalities’ within existing ones. Thus, a new framework to guide public policies
must account for the role of the state in directing investments, creating markets, taking on risks
and uncertainties as lead investor—with private companies only entering later. This expanded role
of the state can build on several ‘heterodox’ economics literatures which have emphasised the
state’s ‘transformational’ capacity.
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4. INSIGHTS ON MARKET SHAPING/CREATING FROM ALTERNATIVE THEORIES
Private business investment in innovation is driven not by costs but by perception of technological
and market opportunities. Studies in industry dynamics have documented that there is a weak
relationship between entry of new firms into industries, and the current levels of profits in those
industries (Vivarelli, 2013). What seems to drive firm entry are the expectations about future
growth opportunities, even if such expectations are often too optimistic (Dosi and Lovallo, 1998).
And such technological and market opportunities have historically been actively shaped by
government spending (Mazzucato, 2013a). This is not to say that the private sector is not
important—of course it is—but historically it has tended to enter new sectors only after the high
uncertainty (e.g. areas of capital intensity, and areas of high risk) were absorbed by the public
sector. This was the case for the IT revolution (Block and Keller, 2012), the biotechnology industry
(Lazonick and Tulum, 2011), for nanotechnology (Motoyama et al, 2011), and for the emerging
clean tech sector (Mazzucato and Penna, 2014).
To develop a transformational market creation/shaping policy framework I draw on insights from
different bodies of thought that have considered the role of the state in the process of fostering
innovation-led growth. These are: (a) science and technology policy research (on mission-oriented
policies); (b) development economics (on ‘developmental states’); (c) evolutionary economics (on
shifts in technological trajectories and techno-economic paradigms); and (d) my own work
(Mazzucato, 2013a) on the ‘Entrepreneurial State’ on the lead risk-taking role of government. The
fact these theories have not been linked and have not been clearly positioned to critique the key
tenets of market failure theory has prevented them from having the impact they could have had
on our understanding of how to guide, evaluate and manage public policy.
a) Science and Technology Policy Research: Mission-Oriented Innovation Policy
The history of innovation policy, studied especially through the ‘systems of innovation’ approach
(Freeman, 1995), provides key insights into the limits of market failure theory in justifying the
depth and breadth of investments that have been necessary for the emergence of radical
technological change. Innovation policy has historically taken the shape of measures that (1)
support basic research, (2) aim to develop and diffuse general-purpose technologies, (3) develop
certain economic sectors that are crucial for innovation, and (4) promote infrastructural
development (Freeman & Soete, 1997 [1974]). The justification of innovation policies have
changed over time: in the 1950s and 1960s, military motives predominated, while the aim since
the 1970s has been to improve economic and competitive positions. In the 1980s, innovation
policy became increasingly justified due to ‘market failure’. The kind of innovation policies driven
by military motives has been described as ‘mission-oriented’ because they aimed to achieve
clearly defined technical goals. In recent years, there have been calls for a return to such policies
to address ‘grand societal challenges’ (Mowery et. al, 2010). However, Foray et al. (2012) contrast
missions of the past, such as putting a man on the moon, with such contemporary missions as
tackling climate change. While missions of the past aimed to develop a particular technology (with
the achievement of the technological objective signalling that the mission was accomplished),
contemporary missions address broader and more persistent challenges, which require long-term
commitments to the development of technological solutions. Indeed, the Maastricht
Memorandum (Soete & Arundel, 1993) provided a detailed analysis of the differences between
‘old’ and ‘new’ mission-oriented projects, showing that “older projects developed radically new
technologies through government procurement projects that were largely isolated from the rest
of the economy, though they frequently affected the structure of related industries and could lead
to new spin-off technologies that had wide-spread effects on other sectors. In contrast,
12
[contemporary] mission-oriented environmental [and other] projects will need to combine
procurement with many other policies in order to have pervasive effects on the entire structure of
production and consumption within an economy” (p. 50). While many mission-oriented policies
used to be tied to military motives (such as the origin of DARPA in the US Department of Defence),
they have more recently been used to set up dynamic public agencies in other mission-oriented
areas like energy security (ARPA-E) and health (National Institutes of Health, NIH). Indeed, the NIH
is the second biggest pot of innovation funding after the Department of Defence, with spend in
2012 reaching $32billion. Angell (2005) claims that such expenditures are the source of most of
the radical innovations in the sector, i.e. new molecular entities with priority rating (with private
pharma focusing more on the incremental drugs and on development).
The mission-oriented literature has developed many useful empirical studies, such as analysis of
different technology policy initiatives in the USA (Chiang, 1991; Mowery et al., 2010), in France
(Foray, 2003), in the UK (Mowery et al., 2010), and in Germany (Cantner & Pyka, 2001); and
studies of mission-oriented agencies and policy programs, including military R&D programs
(Mowery, 2010), the National Institutes of Health (Sampat, 2012); grand missions of agricultural
innovation in the USA (Wright, 2012); and energy (Anadón, 2012), among others. However, the
literature has not integrated the empirical insights to provide a fully-fledged theory that contrasts
its position to that of the four market failure categorisations discussed above. Consequently, the
studies have resulted in ad-hoc theoretical understandings and policy advice on how to manage
mission-oriented initiatives, without tackling the key justifications for mission-oriented
investments in a way that contrasts the justifications to those of market failure. In particular, the
framework has been limited to looking at agencies that focus on science, technology and
innovation policies. Doing so ignores the relationship between types of finance and innovation
development, and overlooks, for example, the rise of public financial institutions like state
investment banks (such as KfW in Germany or the China Development Bank, Sanderson &
Forsythe, 2013 ) as sources of mission-oriented finance, especially as private finance has
increasingly ‘retreated’ from nurturing the ‘real economy’ (Mazzucato; 2013b; Mazzucato and
Penna, 2014). While mission-oriented programs are intrinsically dynamic, with feedback loops
between missions and achievements, the tools used to evaluate such public policies have
remained static, coming from the market failure theory toolbox (despite the fact that many
studies draw on the innovation systems perspective from evolutionary economics). For these
reasons, mission-oriented policy research is currently confined to a small area of policy research
and practice, and has had very little impact on how economists understand the role of public
policy. One particular limitation is that this stream of research has continued to assume that
innovation and dynamism are housed inside firms, with the state only playing a facilitating role. A
new framework must thus seek to address the mismatch between theory and practice by
developing a new economic policy framework that is able to explain and justify the kinds of
mission-oriented policies that have led to the shaping and creation of new markets, and not to the
correction of markets.
b) Development Economics: Developmental Network States
Work on the ‘developmental state’, a concept from a small group of development economists, has
revealed the importance of the ‘visible hand’ of the state in industrialisation and technological
change (Wade, 1990; Chang, 2002; Amsden, 2001). More recently, this literature has also
emphasised the ‘developmental network state’ as key: a decentralised network of different types
of state agencies that can foster innovation and development. While there has been significant
attention placed on the role of large agencies or institutions (such as DARPA or the NIH) in
historical mission-oriented projects, until recently less focus has been placed on the broader
network of structures, actors, strategies and agencies, such as intelligence distributed amongst
actors and institutions, flat organisational structures, flexibility, and customisation (Perez, 2002).
13
Indeed, many successful cases of innovation and technology policy strategies have been carried
out by networks of decentralised public institutions, which have focused not on creating individual
‘national champion’ firms, but on establishing a constellation of innovative firms (O’Riain, 2004).
This has been the case in East Asia, Finland, Israel, Taiwan, and even in Silicon Valley in the US
(Block and Keller, 2011). Such successful policies have covered a wide range of measures, including
R&D support, training, support for marketing and export, funding programs (including early-stage
venture capital), networking and brokerage services, building of facilities and clusters (‘science
parks’), and fostering industrial ties. Not all networks of decentralised institutions were driven by a
technological mission, but this has been the case with the networks fostered by DARPA (driven by
security mission) or the NIH (health/cure of diseases), two of the most successful cases of missionoriented initiatives. In the case of East Asia, the implicit mission was industrial development and
‘catching up’ (Chang, 2002).
From this alternative view, economic development is not the result of natural (exogenous and exante) competitive advantages, but of the endogenous creation of new opportunities that lead to
the establishment of competitive advantages. This requires discovering the cost structure of an
economy in order to identify which types of goods and services that already exist in world markets
can be produced in a domestic economy at low cost (Rodrik, 2004). The state plays a central
coordinating role in this discovery process, and often represents a lead agent in economic
development efforts. To do this, the state may work as an agency to nurture nascent or
knowledge intensive firms (‘infant-industry promotion’); promote strategic trade (such as import
substitution) and financial leverage; prioritise investments in existing strategic sectors (reinforcing
comparative advantages); create ‘national champions’; and provide coherence to economic
policies (Wade, 1990; Amsden, 2001; Chang, 2002; Reinert, 2007; Falck et al., 2011). While the
need for some of these activities may be explained by market failure theory (for example, infantindustry promotion as a result of adverse selection by private investors), by fulfilling this
developmental role, the state does much more than just provide financial capital to fix failures.
Because economic development is an endogenous process, the state provides social capital,
coordinates initiatives and public-private partnerships, fosters synergies, and promotes the
introduction of ‘new combinations’ that create Schumpeterian rents (Reinert, 2007).
c) Evolutionary Economics: Technological Trajectories and Techno-Economic Paradigm Shifts
Schumpeter warned that the methodology of neoclassical economics (based on ‘comparative
statics’; that is, the comparison of static equilibrium situations) and its treatment of technical
change as an exogenous process—both of which market failure theory adopts—were “not
sufficient to explain the real development of the economy” (Schumpeter, 2002 [1912], p. 97).
Evolutionary economists following the Schumpeterian tradition aimed to ‘open the black box of
technical change’ (Rosenberg, 1982) by means of a different methodology (based on historical
analysis and empirical evidence) in order to understand the process that links technical change
(innovation), economic growth and development. Key concepts developed in evolutionary
economics are those of ‘technological paradigms’ and ‘technological trajectories’ (Dosi, 1982;
Nelson and Winter, 1982), which reveal the limitation of market forces in providing a direction to
economic development. A technological paradigm has a threefold definition (Dosi, 1982, p. 148): it
is an outlook of the relevant productive problems confronted by firms (as producers of
technologies or innovators); it represents a set of procedures (routines) of how these problems
shall be approached; and it defines the relevant problems and associated knowledge necessary for
their solution. A technological trajectory, in turn, represents the direction of progress within a
technological paradigm. Therefore, technology development is a problem-solving activity, and a
technological paradigm “embodies strong prescriptions on the directions of technical change” (p.
152). This is why market signals are limited in terms of providing direction to techno-economic
development; they only work within the parameters of the paradigm, and thus influence more the
14
rate of change than its direction. When two or more technological paradigms compete, markets
may influence which one is selected (the one which minimises costs). Once established, however,
paradigms have a powerful ‘exclusion effect’, whereby some technological possibilities are
discarded because they are incompatible with the prevailing paradigm and are therefore ‘invisible’
to agents. Thus, a techno-economic system of innovation may be locked into a self-reinforcing,
path-dependent trajectory (Dosi & Nelson,1994). This becomes a problem if the trajectory being
followed (or the paradigm itself) is inferior or suboptimal to what could be achieved with
technologies that transgress the paradigm (or with a different paradigm).
Perez (2002) expands the notion of technological paradigm to ‘techno-economic paradigm’ in
order to account for the non-technological forces (economic and social institutions) that
characterise certain periods of capitalist history and affect both the economic and social systems.
Her theory of ‘techno-economic paradigm’ shifts is a historical perspective on the long-waves of
development that accompany technological revolutions. “A techno-economic paradigm is, then, a
best-practice model made up of a set of all-pervasive generic technological and organisational
principles, which represent the most effective way of applying a particular technological
revolution and of using it for modernising and rejuvenating the whole of the economy” (Perez,
2002, p. 15). When a new technological revolution emerges, the socio-economic system remains
stuck within the bounds of the previous paradigm, which means that market forces are incapable
of directing the system towards the new paradigm and the modernising and rejuvenating
potential of the new revolution is stifled. In other words, there are mismatches between elements
of the social and techno-economic systems (for example, social expectations, R&D routines, tax
regimes, labour regulations, etc.). In order to overcome these mismatches, it is necessary to build
new institutions that favour the diffusion of the new paradigm. In all previous technological
revolutions, governments have led the process of institution-building that allowed new technoeconomic paradigms to replace the old ones. Perez (2002) specifically points to the role of public
policy in allowing the full deployment of technological revolutions, such as the effect of
suburbanization on the ability of the mass production revolution to diffuse throughout the
economy.
This stream of research on technological and techno-economic paradigms highlights the
importance of cognition when establishing the direction of technological change. Paradigms are
powerful enabling and constraining institutions that favour certain directions of techno-economic
development and obstruct others. In order to redirect techno-economic development on a new,
qualitatively different route, we need a paradigm shift that will avoid the constant renewal of
prevailing trajectories, which happens if market forces provide directionality to the system. From
this perspective, the state has a crucial role to play, in terms of creating a new vision that will
coordinate cognitive efforts of different (public and private) agents and direct their action to areas
beyond the existing paradigm. ‘Green’ innovation can be understood as a redirection of the full
deployment of the IT revolution (Perez, 2010). To be effective in providing the direction of change,
a vision must be created and shared. Stirling (2008) rightly focuses on the role of bottom-up
participatory processes to ensure directionality is taken seriously and shared amongst actors.
d) ‘The Entrepreneurial State’: the State as Lead Risk-Taker and Investor in the Economy
In the book The Entrepreneurial State: Debunking Public vs. Private Sector Myths (Mazzucato,
2013a), I described the risk-taking role the state has played in the few countries that have
achieved innovation-led growth. I focused on the way in which the state played a lead investment
role across the entire innovation chain, from basic research to early-stage seed financing of
companies. I argued that ignoring the high risk and uncertainty that the state has absorbed has
caused the fruits of innovation-led growth to be privatised, even though the underlying risk was
socialised. It is usually assumed that the returns to the state will occur through higher tax income.
However, I argued that this return-generating system is broken, and suggested that more thinking
15
is needed on concrete ways in which direct mechanisms can be generated for the state to create a
‘revolving fund’, so that inevitable losses (innovation is uncertain) can be covered, and the next
round funded—as is the case with private venture capital. A key area of research that is needed is
the accumulation of evidence from across the world on how such return-generating mechanisms
are used, and to consider the implications of the state as a (sort of) public venture capitalist, which
can follow a portfolio approach allowing the returns from the successes to cover the losses from
the failures—with enough left over to cover the next round of investments. How to do this while
also retaining a mission-oriented perspective (not limited by cost-benefit analysis), is a key
challenge.
5. BEYOND MARKET FAILURE: ROUTES, ORGANISATION, ASSESSMENT & REWARDS
This section brings together key concepts from the four heterodox frameworks reviewed above,
drawing especially on the empirical research done within these, in order to provide a new
theoretical conceptualisation for guiding state action to tackle transformational change.
Directionality: the role of the state beyond fixing market failures. Policies that aim to correct
markets assume that once the sources of the failure have been addressed, market forces will
efficiently direct the economy to a path of growth and development. Yet, markets are ‘blind’ (Dosi,
1982) and the direction of change provided by markets often represents suboptimal outcomes
from a societal point of view. This is why, in addressing societal challenges, states have sometimes
led the process and provided the direction towards new ‘techno-economic paradigms’, which did
not come about spontaneously out of market forces. In the mass production revolution and the IT
revolution, governments made direct investments in the technologies that enabled these
revolutions to emerge, and formulated bold policies that allowed them to be fully deployed
throughout the economy (Ruttan, 2006; Block and Keller, 2011). Examples include suburbanisation
policies that allowed mass production to affect the productivity of all sectors, or the military
motives that allowed IT to begin its deployment phase (Perez, 2002). Furthermore, in the IT
revolution, and even in the emerging clean tech revolution, government not only funded the
actual technologies (such as mainframes, the Internet, wind and solar power, and fuel cells), but
also provided early-stage funding to companies that risk-averse private finance would not, and
devised special tax credits that favoured some activities more than others (Mazzucato, 2013a).
These facts seem to point to a different analytical problem facing policy makers: choosing whether
the right role is to direct or stand back, understanding how particular ‘directions’ and routes can
be picked, and determining how to mobilise and manage activities that can lead to the
achievement of dynamic social and technological challenges.
The problem is not whether to pick or not to pick a direction but how to learn from the successful
picking of the past, and to enable the directions picked to be broad enough to allow bottom up
exploration, discovery and learning. This is sometimes referred to as ‘smart specialisation’ (Foray,
David and Hall, 2009). Smart specialisation is explicitly a results and outcome oriented agenda not
input or outputs oriented agenda (Rodrik, 2004). Yet the fact it has until now been based on a
market failure framework means that at best its seen as a ‘discovery’ process for stakeholders and
policy-designers to identify together different bottlenecks, market failures, and missing links.
What it has not addressed is the way in which innovation-led growth in places like Silicon Valley
actually happened - requiring not only identifying missing links but forming concrete strategies
towards producing market landscapes that simply did not exist.
Organisation: learning, experimentation and self-discovery. If brought to its extreme, as
advocated by critics from Public Choice and the Chicago School of Economics, market failure
theory calls for the state to intervene as little as possible in the economy, in a way that minimises
the risk of ‘government failure’, from crowding out to cronyism and corruption. This view requires
16
a structure that insulates the public sector from the private sector (to avoid issues such as agency
capture) and has resulted in a trend of ‘outsourcing’ that often rids government of the knowledge
capacities and capabilities (for example, around IT) that are necessary for managing change
(Kakabadse & Kakabadse, 2002). Studies have examined the influence of outsourcing on the ability
of public institutions to attract top-level talent with the relevant knowledge and skills to manage
transformative mission-oriented policies. Without such talent and expertise it is nearly impossible
for the state to fulfil its role of coordination and provision of direction to private actors when
formulating and implementing policies that address societal challenges. In order to promote
transformation of the economy, by shaping and creating technologies, sectors and markets, the
state must organise itself so that it has the ‘intelligence’ (policy capacity) to think big and
formulate bold policies. If the state is essential to the process of transformative technological and
socio-economic change, then understanding the appropriate structure of public organisations is
also essential. Innovation is subject to extreme uncertainty, which creates the need for both
patience (‘patient long-term capital’, Mazzucato, 2013b) and the ability to experiment and explore
the underlying landscape (Rodrik, 2004). Therefore, a crucial element in organising the state for its
‘roaring’ role is ‘absorptive capacity’ (Cohen and Levinthal, 1990) so that governmental agencies
learn in a process of investment, discovery and experimentation.
The size of the state, and hence its ability to earn back a return either through tax or other means
to fund its size, depends on its purpose. If the role of the state is to simply correct market failures
and perform a subsidiary role to private initiative, it is sufficient to have little more than a ‘minimal
state’ that performs only ‘unanimously approved’ functions, such as guaranteeing property rights
and enforcing contracts (Atkinson & Stiglitz, 1980). Indeed, the use of market failure as a
diagnostic tool for public policies became prominent in the 1980s and was accompanied by public
administration reform initiatives that sought to ‘modernise’ (often through downsizing) the state
apparatus (Pollitt & Bouckaert, 2004), often in line with tenets from Public Choice theory
(Buchanan, 2003). If policymaking is seen (i) as a non-probabilistic risk-taking process surmounted
by uncertainty about technical and economic outcomes (Mazzucato, 2013a); (ii) as a process of
experimentation and discovery (Hirschman, 1967; Rodrik, 2004); and (iii) as a continuous process
of learning that leads to some successes and failures measured beyond static monetary analysis of
the costs and benefits attached to quantifiable outcomes, then the size of the state apparatus and
purely economic efficiency of the state are the wrong focuses for organising the state.
This suggests that the key concern should be to establish which skills/resources, capabilities and
structures are useful to increase the chances that a state organisation will be effective both in
learning and in establishing symbiotic partnerships with the private sector—and ultimately
succeed in implementing mission-oriented and transformative policies. Furthermore, it is crucial to
explore alternative ways through which the state may engage with and assume risks. It does this
not by adopting a conservative strategy that minimises the risks of picking losing projects and
maximising the probability of picking winners, but by adopting a portfolio approach for its
investments (Rodrik, 2013). In such an approach, (a) success from a few projects can cover the
losses from many projects and (b) the state learns from its losing investments (Mazzucato, 2013a).
What matters in this approach is not so much the matching between failures and fixes, but an
institutional structure that ensures winning policies provide enough ‘rewards’ to cover the losses,
and that losses are used as learning cases to improve and renew future policies. The work on the
developmental state (Block and Keller, 2012) suggests that these goals are best achieved not
through a top down policies but through a decentralised structure where the organisation/s
involved remain nimble, innovative and dynamic from within.
Evaluation: static vs. dynamic metrics. The market failure framework has developed concrete
indicators and methods to evaluate government investments, which stem directly from the
framework itself, usually through a cost-benefit analysis that estimates whether the benefits of
17
public intervention compensate for the costs associated both with the market failure and the
implementation of the policy (including ‘governmental failures’). However, there is a mismatch
between the intrinsically dynamic character of economic development and the static tools with
which the role of the state in the process is evaluated. The mainstream diagnostics and evaluation
approach (based on market failure theory) involves identifying the sources of the market failure
and targeting policy interventions on their correction. It mostly entails ex-ante considerations
about administrative and fiscal requirements and political–economic consequences of the
intervention (Rodrik, 2004). Such an exercise usually consists of the following steps:
An ex-ante cost-benefit analysis that weighs up the costs of the failure, the (private and social)
benefits from addressing it, and the costs and risks of government failure.
An ex-ante identification of sources of market failures and of second-best policy tools to
address them.
An ex-ante diagnostic of the best principal–agent structure that avoids governmental capture
by private interests (insulation/autonomy) and that forces private agents to do what the
principal (government) wants.
An ex-post evaluation of the outcomes of the intervention vis-à-vis the ex-ante quantifiable
prediction of the likely outcomes of the intervention.
This is a limited toolbox for evaluating public policies and investments that aim to address societal
challenges, because doing so represents a static exercise of evaluation of an intrinsically dynamic
process. By not allowing for the possibility that government can transform and create new
landscapes that did not exist before, the ability to measure such impact has been affected, with
economists often resorting to an analysis of the public sector as an inefficient private one
(Mazzucato, 2013a). This is evident not only in the area of innovation, but also for public services.
This then leads to accusations of government ‘crowding out’ businesses, which implies that those
areas that government moves into could have been areas for business investment. Such
accusations are best defended through a ‘crowding in’ argument, which rests on showing how
government investments create a large pie of national output that can be shared (the savings)
between private and public investors. However, this defence does not capture the fact that
businesses are risk-averse and unwilling or unable to transform existing and create new
landscapes (which is about creating new pies, not increasing existing pies). By not having
indicators for such transformative action, the toolbox affects the government’s ability to know
when it is simply operating in existing spaces or making new things happen that would not have
happened anyway (its ‘additionality’). This often leads to investments that are too narrow or
directed within the confines of the boundaries set by business practices of the prevailing technoeconomic paradigm (Abraham, 2010).
It is thus crucial to develop a new toolbox and indicators with which to evaluate and measure the
degree to which state investments open up and transform sectoral and technological landscapes,
rather than operating within existing ones. The indicators must take into account the underlying
risk and uncertainty in transforming such landscapes.
Risks and Rewards: towards symbiotic private–public partnerships. Market failure theory says
little about cases in which the state is the lead investor and risk taker in capitalist economies.
Having a vision of which way to drive an economy requires direct and indirect investment in
particular areas, not just ‘creating the conditions’ for change. This requires crucial choices to be
made, the fruits of which will create some winners, but also many losers. For example, the Obama
administration in the US recently provided a large guaranteed loans to two green-tech companies,
Solyndra ($500 million) and Tesla Motors ($465 million). While the latter is often glorified as a
success story, the former failed miserably and became the latest example, used widely by both
economists and the more popular treatment by the media, of government being unable to ‘pick
18
winners’. Indeed, the taxpayer picked up the bill (Wood, 2012), and complained. This suggests the
need for such investments to be made in a portfolio approach with some of the upside gains
covering the downside losses. That is, if the public sector is expected to fill in for the lack of private
VC money going to early stage innovation, it should at least be able to benefit as private VC does
from the wins. Otherwise, the funding for such investments cannot be secured.
Yet questions about risks and rewards depend on the underlying framework through which public
investment is justified. In a market-shaping framework, does government deserve to retain equity
more than in a market failure framework? Are taxes currently bringing back enough return to
government budgets to fund high-risk investments that will probably fail? Using a portfolio
approach to public investments (Rodrik, 2013) means being able to reap back a reward from the
wins, in order to fund the losses and the next round. Such direct return-generating mechanisms
must be explored, including retaining equity, golden share of the IPR, and income-contingent
loans, among others (Mazzucato, 2013).
Sharing risks and rewards also requires making sure that private sector commitment to innovation
increases not falls. As recently emphasised by an MIT report on the innovation economy, today’s
capitalism is missing the kind of large company engagement of the sort that Xerox Parc and Bell
Labs played in the past. In looking at the strengths and weaknesses of the US innovation system and
the causes of relative decline of manufacturing in America, the study has strived to understand why
the development of promising innovations are stalling or simply moving abroad before reaching
commercial scale—a problem even more central to the UK economy. One of the reasons unveiled
by the study is the fact that large private R&D centres – like Bell Labs, Xerox PARC and Alcoa
Research Lab – have become a thing of the past in big corporations; they have mostly
disappeared. Long-term basic and applied research is not part of the strategy of ‘Big Business’
anymore, as corporate R&D now focuses on short-term needs (MIT, 2013). Recent examples of
extreme financialization of large corporations, in areas as different as pharmaceuticals, IT and
energy, is putting the development of proper innovation eco-systems at risk (Lazonick and
Mazzucato, 2013). Financialization is most evident with the amount of profits being used to boost
share prices (and stock options hence executive pay) through activities like share-buybacks (Figure
6 shows how repurchases of their own shares by the Fortune 500 companies reached $3 trillion
dollars in the last decade)—with the most worrying aspect the degree to which such expenditure
has outpaced R&D. Part of getting the risk-reward balance right must thus consist not only of
allowing the public sector to reap its deserved reward for winning investments (to cover the
inevitable losses, and the next round of investments) but also to increase the actual risks taken by
large companies in the innovation process. This means that innovation policy and policies around
financial reform and corporate governance should be brought together so the eco-systems of
innovation (and associated private-public partnerships) that we build are more symbiotic and less
parasitic.
19
Figure 6 Rising share buyback trend: Repurchases (RP), Net Income (NI), Total Dividends (TD), R&D
(source: calculations from work of Lazonick, 2014)
6. CONCLUSION
This paper has considered the limitations of the market failure framework that continues to guide
innovation policy. It has argued that putting innovation at the centre of growth policy requires an
emphasis on shaping and creating markets not only fixing them. To facilitate this change—the goal
of this think piece—the paper has considered insights from alternative (heterodox) literatures in
the economics of innovation on this market creation process.
Considering the need for government policy to ‘transform’, be catalytic, create and shape markets
not just fix them, helps reframe the key questions of economic policy from static ones that worry
about crowding out and picking winners to more dynamic ones that are constructive in forming the
types of public–private interactions that can create new innovation and industrial landscapes. In
this perspective, it is key for government to not just pick different technologies or sectors but ask
what it wants from those sectors. In the same way that putting a man on the moon required many
sectors to interact, the ‘green’ direction being debated today also requires all sectors to change.
Green is not only about wind, solar and biofuels but also about new engines, new maintenance
systems, new ways of thinking about product obsolescence (Mazzucato and Perez, 2014). This is
not about prescribing specific technologies, but providing directions of change which bottom up
solutions can then experiment around. As Stirling (2014, p.2) has recently put it: ‘The more
demanding the innovation challenges like poverty, ill health or environmental damage, the greater
becomes the importance of effective policy. This is not a question of “picking winners”—an
uncertainty-shrouded dilemma which is anyhow equally shared between public, private and third
sectors. Instead, it is about engaging widely across society, in order to build the most fruitful
conditions for deciding what “winning” even means’.
It has been argued here that government would benefit from adopting a portfolio approach to
public investments in innovations, nurturing the explorative, plural, and trial and error aspect of
change. This requires thinking not only about technological change in a new way but also
organizational change. Building the public agencies of the future with creative, adaptive and
explorative capacity.
In sum, this paper has argued that to approach the innovation challenge of the future, we must
open up the discussion, away from the narrow worry about ‘picking winners’ and ‘crowding out’,
towards a broader focus on four interlinked dynamic questions:
20
Directions. How can public policy be understood in terms of setting the direction and route of
change; that is, shaping and creating markets rather than just fixing them? What can be
learned from the ways in which directions were set in the past, and how can we stimulate more
democratic debate about such directionality?
Evaluation. How can an alternative conceptualisation (to standard market failure theory) of the
role of the public sector in the economy translate into new indicators and assessment tools for
evaluating public policies, beyond the micro-economic cost/benefit analysis? How does this
alter the crowding in/out narrative?
Organisational change. How should public organisations be structured so they accommodate
the risk-taking and explorative capacity, and the capabilities needed to envision and manage
contemporary challenges?
Risks and Rewards. How can this alternative conceptualisation be put into practice so that it
frames investment tools so that they not only socialise risk but also have potential to socialise
the rewards that enable ‘smart growth’ to also be ‘inclusive growth’?
21
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